Overview

Dataset statistics

Number of variables20
Number of observations71
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.6 KiB
Average record size in memory168.0 B

Variable types

Text1
Numeric19

Alerts

Mar Cap Rs.Cr. is highly overall correlated with NP 2Qtr Bk Rs.Cr. and 15 other fieldsHigh correlation
NP 2Qtr Bk Rs.Cr. is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
NP 3Qtr Bk Rs.Cr. is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
NP Prev Qtr Rs.Cr. is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
NP Qtr Rs.Cr. is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
OP 2Qtr Bk Rs.Cr. is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
OP 3Qtr Bk Rs.Cr. is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
OP Prev Qtr Rs.Cr. is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
OP Qtr Rs.Cr. is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
Sales 2Qtr Bk Rs.Cr. is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
Sales 3Qtr Bk Rs.Cr. is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
Sales Prev Qtr Rs.Cr. is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
Sales Qtr Rs.Cr. is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
expenses_Prev_Qtr_Cr is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
expenses_Qtr_Cr is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
other_effect_Prev_Qtr_Cr is highly overall correlated with other_effect_Qtr_CrHigh correlation
other_effect_Qtr_Cr is highly overall correlated with other_effect_Prev_Qtr_CrHigh correlation
profit_before_tax_Prev_Qtr_Cr is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
profit_before_tax_Qtr_Cr is highly overall correlated with Mar Cap Rs.Cr. and 15 other fieldsHigh correlation
Name has unique valuesUnique
Mar Cap Rs.Cr. has unique valuesUnique
NP Qtr Rs.Cr. has unique valuesUnique
Sales Qtr Rs.Cr. has unique valuesUnique
Sales Prev Qtr Rs.Cr. has unique valuesUnique
NP 2Qtr Bk Rs.Cr. has unique valuesUnique
NP 3Qtr Bk Rs.Cr. has unique valuesUnique
NP Prev Qtr Rs.Cr. has unique valuesUnique
Sales 2Qtr Bk Rs.Cr. has unique valuesUnique
Sales 3Qtr Bk Rs.Cr. has unique valuesUnique
OP Prev Qtr Rs.Cr. has unique valuesUnique
OP 2Qtr Bk Rs.Cr. has unique valuesUnique
OP 3Qtr Bk Rs.Cr. has unique valuesUnique
OP Qtr Rs.Cr. has unique valuesUnique
profit_before_tax_Qtr_Cr has unique valuesUnique
profit_before_tax_Prev_Qtr_Cr has unique valuesUnique
other_effect_Prev_Qtr_Cr has unique valuesUnique
expenses_Qtr_Cr has unique valuesUnique
expenses_Prev_Qtr_Cr has unique valuesUnique

Reproduction

Analysis started2024-02-29 17:22:50.778249
Analysis finished2024-02-29 17:24:27.099868
Duration1 minute and 36.32 seconds
Software versionydata-profiling vv4.6.4
Download configurationconfig.json

Variables

Name
Text

UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-02-29T22:54:27.345535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length13.478873
Min length7

Characters and Unicode

Total characters957
Distinct characters49
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)100.0%

Sample

1st rowRemedium Life
2nd rowWaaree Renewab.
3rd rowDreamfolks Servi
4th rowJyoti Resins
5th rowEsab India
ValueCountFrequency (%)
india 6
 
4.1%
industries 5
 
3.4%
inds 3
 
2.0%
tech 2
 
1.4%
paints 2
 
1.4%
engineering 2
 
1.4%
life 2
 
1.4%
chem 2
 
1.4%
paper 2
 
1.4%
gas 2
 
1.4%
Other values (119) 119
81.0%
2024-02-29T22:54:28.147441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 83
 
8.7%
e 77
 
8.0%
76
 
7.9%
n 70
 
7.3%
i 59
 
6.2%
r 52
 
5.4%
t 47
 
4.9%
s 46
 
4.8%
o 37
 
3.9%
l 35
 
3.7%
Other values (39) 375
39.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 680
71.1%
Uppercase Letter 176
 
18.4%
Space Separator 76
 
7.9%
Other Punctuation 23
 
2.4%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 83
12.2%
e 77
11.3%
n 70
10.3%
i 59
8.7%
r 52
 
7.6%
t 47
 
6.9%
s 46
 
6.8%
o 37
 
5.4%
l 35
 
5.1%
d 27
 
4.0%
Other values (14) 147
21.6%
Uppercase Letter
ValueCountFrequency (%)
I 30
17.0%
S 20
11.4%
A 16
 
9.1%
P 15
 
8.5%
C 12
 
6.8%
L 11
 
6.2%
G 9
 
5.1%
E 8
 
4.5%
T 7
 
4.0%
R 7
 
4.0%
Other values (11) 41
23.3%
Other Punctuation
ValueCountFrequency (%)
. 22
95.7%
& 1
 
4.3%
Space Separator
ValueCountFrequency (%)
76
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 856
89.4%
Common 101
 
10.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 83
 
9.7%
e 77
 
9.0%
n 70
 
8.2%
i 59
 
6.9%
r 52
 
6.1%
t 47
 
5.5%
s 46
 
5.4%
o 37
 
4.3%
l 35
 
4.1%
I 30
 
3.5%
Other values (35) 320
37.4%
Common
ValueCountFrequency (%)
76
75.2%
. 22
 
21.8%
- 2
 
2.0%
& 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 957
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 83
 
8.7%
e 77
 
8.0%
76
 
7.9%
n 70
 
7.3%
i 59
 
6.2%
r 52
 
5.4%
t 47
 
4.9%
s 46
 
4.8%
o 37
 
3.9%
l 35
 
3.7%
Other values (39) 375
39.2%

Mar Cap Rs.Cr.
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18085.813
Minimum1008.85
Maximum302075.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-02-29T22:54:28.572119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1008.85
5-th percentile1115.835
Q12121.105
median6070.05
Q318091.46
95-th percentile63978.55
Maximum302075.36
Range301066.51
Interquartile range (IQR)15970.355

Descriptive statistics

Standard deviation39401.751
Coefficient of variation (CV)2.1786
Kurtosis39.438413
Mean18085.813
Median Absolute Deviation (MAD)4747.44
Skewness5.7456346
Sum1284092.7
Variance1.552498 × 109
MonotonicityNot monotonic
2024-02-29T22:54:28.981363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1054.75 1
 
1.4%
35002.29 1
 
1.4%
24903.2 1
 
1.4%
2129.37 1
 
1.4%
1567.66 1
 
1.4%
9603.8 1
 
1.4%
36163.05 1
 
1.4%
1075.44 1
 
1.4%
27361.23 1
 
1.4%
34432.95 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
1008.85 1
1.4%
1019.61 1
1.4%
1054.75 1
1.4%
1075.44 1
1.4%
1156.23 1
1.4%
1157.41 1
1.4%
1180.74 1
1.4%
1211.71 1
1.4%
1258.43 1
1.4%
1260.76 1
1.4%
ValueCountFrequency (%)
302075.36 1
1.4%
108364.25 1
1.4%
72218.14 1
1.4%
65376.86 1
1.4%
62580.24 1
1.4%
51427.14 1
1.4%
38085.15 1
1.4%
36163.05 1
1.4%
35002.29 1
1.4%
34595.31 1
1.4%

NP Qtr Rs.Cr.
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.39113
Minimum2.99
Maximum1475.16
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-02-29T22:54:29.439862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.99
5-th percentile7.78
Q118.675
median45.86
Q3121.405
95-th percentile455.98
Maximum1475.16
Range1472.17
Interquartile range (IQR)102.73

Descriptive statistics

Standard deviation216.11102
Coefficient of variation (CV)1.7657409
Kurtosis22.530754
Mean122.39113
Median Absolute Deviation (MAD)36.27
Skewness4.2344985
Sum8689.77
Variance46703.973
MonotonicityNot monotonic
2024-02-29T22:54:29.833459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.53 1
 
1.4%
324.09 1
 
1.4%
150.59 1
 
1.4%
8.54 1
 
1.4%
16.01 1
 
1.4%
77.42 1
 
1.4%
113.36 1
 
1.4%
3.46 1
 
1.4%
140.21 1
 
1.4%
124.07 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
2.99 1
1.4%
3.46 1
1.4%
6.53 1
1.4%
7.34 1
1.4%
8.22 1
1.4%
8.54 1
1.4%
9.09 1
1.4%
9.58 1
1.4%
9.59 1
1.4%
10.16 1
1.4%
ValueCountFrequency (%)
1475.16 1
1.4%
754.59 1
1.4%
590.4 1
1.4%
480.5 1
1.4%
431.46 1
1.4%
416.51 1
1.4%
324.09 1
1.4%
296.25 1
1.4%
222.9 1
1.4%
218.55 1
1.4%

Sales Qtr Rs.Cr.
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1049.0531
Minimum34.77
Maximum9103.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-02-29T22:54:30.306661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.77
5-th percentile54.985
Q1147.665
median404.22
Q31055.1
95-th percentile4641.825
Maximum9103.09
Range9068.32
Interquartile range (IQR)907.435

Descriptive statistics

Standard deviation1707.5108
Coefficient of variation (CV)1.6276686
Kurtosis8.4969623
Mean1049.0531
Median Absolute Deviation (MAD)309.07
Skewness2.8109183
Sum74482.77
Variance2915593.1
MonotonicityNot monotonic
2024-02-29T22:54:30.765753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
468.57 1
 
1.4%
1294.8 1
 
1.4%
881.74 1
 
1.4%
95.15 1
 
1.4%
231.91 1
 
1.4%
983.12 1
 
1.4%
4943.18 1
 
1.4%
34.77 1
 
1.4%
1946.58 1
 
1.4%
787.47 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
34.77 1
1.4%
52.44 1
1.4%
53.71 1
1.4%
53.79 1
1.4%
56.18 1
1.4%
59.1 1
1.4%
61.18 1
1.4%
62.96 1
1.4%
69.38 1
1.4%
71.77 1
1.4%
ValueCountFrequency (%)
9103.09 1
1.4%
6988.13 1
1.4%
5174.98 1
1.4%
4943.18 1
1.4%
4340.47 1
1.4%
4265.22 1
1.4%
3925.98 1
1.4%
3845.4 1
1.4%
2116.9 1
1.4%
1946.58 1
1.4%

Sales Prev Qtr Rs.Cr.
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean986.11268
Minimum31.04
Maximum8478.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-02-29T22:54:31.187425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31.04
5-th percentile47.505
Q1164.885
median395.32
Q3976.43
95-th percentile4163.015
Maximum8478.57
Range8447.53
Interquartile range (IQR)811.545

Descriptive statistics

Standard deviation1549.7311
Coefficient of variation (CV)1.5715558
Kurtosis8.595734
Mean986.11268
Median Absolute Deviation (MAD)283.57
Skewness2.7796169
Sum70014
Variance2401666.5
MonotonicityNot monotonic
2024-02-29T22:54:31.628744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
330.46 1
 
1.4%
1239.58 1
 
1.4%
896.2 1
 
1.4%
64.22 1
 
1.4%
628.76 1
 
1.4%
941.77 1
 
1.4%
3271.5 1
 
1.4%
38.24 1
 
1.4%
1782.57 1
 
1.4%
731.38 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
31.04 1
1.4%
31.53 1
1.4%
38.24 1
1.4%
43.64 1
1.4%
51.37 1
1.4%
54.2 1
1.4%
61.18 1
1.4%
64.22 1
1.4%
67.22 1
1.4%
68.9 1
1.4%
ValueCountFrequency (%)
8478.57 1
1.4%
5693.39 1
1.4%
5250.94 1
1.4%
4217.7 1
1.4%
4108.33 1
1.4%
3781.51 1
1.4%
3773.01 1
1.4%
3271.5 1
1.4%
2015.53 1
1.4%
1910.4 1
1.4%

NP 2Qtr Bk Rs.Cr.
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean117.95127
Minimum-4.78
Maximum1574.84
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)1.4%
Memory size1.1 KiB
2024-02-29T22:54:32.039794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-4.78
5-th percentile5.24
Q125.155
median62.38
Q3118.64
95-th percentile380.43
Maximum1574.84
Range1579.62
Interquartile range (IQR)93.485

Descriptive statistics

Standard deviation206.95154
Coefficient of variation (CV)1.7545512
Kurtosis35.564578
Mean117.95127
Median Absolute Deviation (MAD)45.97
Skewness5.3374532
Sum8374.54
Variance42828.938
MonotonicityNot monotonic
2024-02-29T22:54:32.371690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.78 1
 
1.4%
267.66 1
 
1.4%
87.63 1
 
1.4%
33.22 1
 
1.4%
28.3 1
 
1.4%
90.53 1
 
1.4%
80.61 1
 
1.4%
4.77 1
 
1.4%
138.11 1
 
1.4%
119.81 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
-4.78 1
1.4%
1.81 1
1.4%
4.77 1
1.4%
5.16 1
1.4%
5.32 1
1.4%
8.69 1
1.4%
8.8 1
1.4%
8.86 1
1.4%
12.22 1
1.4%
12.27 1
1.4%
ValueCountFrequency (%)
1574.84 1
1.4%
542.8 1
1.4%
403.16 1
1.4%
390.36 1
1.4%
370.5 1
1.4%
320.95 1
1.4%
280.6 1
1.4%
267.66 1
1.4%
246.44 1
1.4%
242.73 1
1.4%

NP 3Qtr Bk Rs.Cr.
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.10141
Minimum0.6
Maximum1258.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-02-29T22:54:32.768026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile9.105
Q123.01
median46.08
Q3114.615
95-th percentile432.69
Maximum1258.41
Range1257.81
Interquartile range (IQR)91.605

Descriptive statistics

Standard deviation186.3045
Coefficient of variation (CV)1.6472341
Kurtosis20.333857
Mean113.10141
Median Absolute Deviation (MAD)34.99
Skewness3.9428227
Sum8030.2
Variance34709.366
MonotonicityNot monotonic
2024-02-29T22:54:33.228821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.52 1
 
1.4%
352.46 1
 
1.4%
106.1 1
 
1.4%
16.97 1
 
1.4%
25.21 1
 
1.4%
106.21 1
 
1.4%
51.89 1
 
1.4%
9.12 1
 
1.4%
128.61 1
 
1.4%
107.1 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
0.6 1
1.4%
1.52 1
1.4%
7.68 1
1.4%
9.09 1
1.4%
9.12 1
1.4%
9.26 1
1.4%
10.28 1
1.4%
10.54 1
1.4%
11.09 1
1.4%
11.68 1
1.4%
ValueCountFrequency (%)
1258.41 1
1.4%
529.63 1
1.4%
526.85 1
1.4%
436.96 1
1.4%
428.42 1
1.4%
371.57 1
1.4%
352.46 1
1.4%
351.8 1
1.4%
310.98 1
1.4%
219.42 1
1.4%

NP Prev Qtr Rs.Cr.
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean110.93676
Minimum-3.37
Maximum1232.39
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)1.4%
Memory size1.1 KiB
2024-02-29T22:54:33.666520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3.37
5-th percentile5.75
Q117.575
median47.9
Q3116.08
95-th percentile431.9
Maximum1232.39
Range1235.76
Interquartile range (IQR)98.505

Descriptive statistics

Standard deviation183.59476
Coefficient of variation (CV)1.6549497
Kurtosis19.935186
Mean110.93676
Median Absolute Deviation (MAD)33.41
Skewness3.9120653
Sum7876.51
Variance33707.035
MonotonicityNot monotonic
2024-02-29T22:54:34.119323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.25 1
 
1.4%
272.52 1
 
1.4%
142.32 1
 
1.4%
-3.37 1
 
1.4%
27.57 1
 
1.4%
75.18 1
 
1.4%
67.19 1
 
1.4%
4.18 1
 
1.4%
121.39 1
 
1.4%
112.04 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
-3.37 1
1.4%
4.18 1
1.4%
5.25 1
1.4%
5.65 1
1.4%
5.85 1
1.4%
6.79 1
1.4%
8.38 1
1.4%
9.03 1
1.4%
11.1 1
1.4%
11.92 1
1.4%
ValueCountFrequency (%)
1232.39 1
1.4%
577.27 1
1.4%
494.03 1
1.4%
434.03 1
1.4%
429.77 1
1.4%
382.9 1
1.4%
328.5 1
1.4%
278.35 1
1.4%
272.52 1
1.4%
215.95 1
1.4%

Sales 2Qtr Bk Rs.Cr.
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean998.96352
Minimum10.22
Maximum9182.31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-02-29T22:54:34.598861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10.22
5-th percentile44.4
Q1171.965
median411.67
Q3995.58
95-th percentile4179.37
Maximum9182.31
Range9172.09
Interquartile range (IQR)823.615

Descriptive statistics

Standard deviation1569.814
Coefficient of variation (CV)1.5714428
Kurtosis10.863079
Mean998.96352
Median Absolute Deviation (MAD)316.68
Skewness3.0089617
Sum70926.41
Variance2464316
MonotonicityNot monotonic
2024-02-29T22:54:35.005706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75.58 1
 
1.4%
1273.57 1
 
1.4%
762.32 1
 
1.4%
168.84 1
 
1.4%
659.54 1
 
1.4%
974.47 1
 
1.4%
3065.45 1
 
1.4%
35.73 1
 
1.4%
1954.53 1
 
1.4%
742.59 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
10.22 1
1.4%
30.2 1
1.4%
35.73 1
1.4%
40.89 1
1.4%
47.91 1
1.4%
49.38 1
1.4%
61.49 1
1.4%
65.08 1
1.4%
68.81 1
1.4%
68.9 1
1.4%
ValueCountFrequency (%)
9182.31 1
1.4%
5475.82 1
1.4%
4694.4 1
1.4%
4270.16 1
1.4%
4088.58 1
1.4%
3928.57 1
1.4%
3889.38 1
1.4%
3065.45 1
1.4%
1954.53 1
1.4%
1928.54 1
1.4%

Sales 3Qtr Bk Rs.Cr.
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1002.449
Minimum5.93
Maximum8787.34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-02-29T22:54:35.508497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.93
5-th percentile52.6
Q1170.755
median388.4
Q31059.08
95-th percentile4160.86
Maximum8787.34
Range8781.41
Interquartile range (IQR)888.325

Descriptive statistics

Standard deviation1671.8207
Coefficient of variation (CV)1.6677364
Kurtosis10.877681
Mean1002.449
Median Absolute Deviation (MAD)297.6
Skewness3.1356111
Sum71173.88
Variance2794984.6
MonotonicityNot monotonic
2024-02-29T22:54:36.044165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
176.48 1
 
1.4%
1226.85 1
 
1.4%
792.71 1
 
1.4%
114.31 1
 
1.4%
552.09 1
 
1.4%
1080.26 1
 
1.4%
2404.72 1
 
1.4%
36.88 1
 
1.4%
1784.32 1
 
1.4%
675.26 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
5.93 1
1.4%
26.56 1
1.4%
36.88 1
1.4%
52.38 1
1.4%
52.82 1
1.4%
60.84 1
1.4%
66.36 1
1.4%
66.61 1
1.4%
67.33 1
1.4%
68.27 1
1.4%
ValueCountFrequency (%)
8787.34 1
1.4%
8309.59 1
1.4%
4518.72 1
1.4%
4323.68 1
1.4%
3998.04 1
1.4%
3942.37 1
1.4%
3684.29 1
1.4%
2404.72 1
1.4%
2260.78 1
1.4%
1811.75 1
1.4%

OP Prev Qtr Rs.Cr.
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162.81085
Minimum-0.33
Maximum1716.23
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)1.4%
Memory size1.1 KiB
2024-02-29T22:54:36.463993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-0.33
5-th percentile9.81
Q126.11
median71.41
Q3191.065
95-th percentile657.245
Maximum1716.23
Range1716.56
Interquartile range (IQR)164.955

Descriptive statistics

Standard deviation257.35189
Coefficient of variation (CV)1.5806803
Kurtosis18.848393
Mean162.81085
Median Absolute Deviation (MAD)51.77
Skewness3.7623824
Sum11559.57
Variance66229.997
MonotonicityNot monotonic
2024-02-29T22:54:37.027266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.28 1
 
1.4%
343.04 1
 
1.4%
232.11 1
 
1.4%
-0.33 1
 
1.4%
41.5 1
 
1.4%
123.18 1
 
1.4%
131.87 1
 
1.4%
6.71 1
 
1.4%
203.86 1
 
1.4%
219.98 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
-0.33 1
1.4%
6.71 1
1.4%
7.28 1
1.4%
9.77 1
1.4%
9.85 1
1.4%
11.16 1
1.4%
13.02 1
1.4%
16.61 1
1.4%
17 1
1.4%
17.78 1
1.4%
ValueCountFrequency (%)
1716.23 1
1.4%
743.53 1
1.4%
721.27 1
1.4%
705.57 1
1.4%
608.92 1
1.4%
467.8 1
1.4%
424.6 1
1.4%
394.52 1
1.4%
388 1
1.4%
346.12 1
1.4%

OP 2Qtr Bk Rs.Cr.
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean164.26789
Minimum-2.9
Maximum2121.29
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)1.4%
Memory size1.1 KiB
2024-02-29T22:54:37.542235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-2.9
5-th percentile7.45
Q132.615
median76.93
Q3170.955
95-th percentile520.54
Maximum2121.29
Range2124.19
Interquartile range (IQR)138.34

Descriptive statistics

Standard deviation285.66673
Coefficient of variation (CV)1.7390296
Kurtosis31.865884
Mean164.26789
Median Absolute Deviation (MAD)57.58
Skewness5.0185268
Sum11663.02
Variance81605.478
MonotonicityNot monotonic
2024-02-29T22:54:37.974098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-2.9 1
 
1.4%
315.74 1
 
1.4%
163.64 1
 
1.4%
35.7 1
 
1.4%
42.55 1
 
1.4%
134.51 1
 
1.4%
156.29 1
 
1.4%
7.01 1
 
1.4%
178.27 1
 
1.4%
202.59 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
-2.9 1
1.4%
3.33 1
1.4%
7.01 1
1.4%
7.04 1
1.4%
7.86 1
1.4%
12.2 1
1.4%
13.18 1
1.4%
14 1
1.4%
14.84 1
1.4%
15.98 1
1.4%
ValueCountFrequency (%)
2121.29 1
1.4%
844.78 1
1.4%
560.32 1
1.4%
548.56 1
1.4%
492.52 1
1.4%
490.79 1
1.4%
423.89 1
1.4%
386.63 1
1.4%
357.23 1
1.4%
342.8 1
1.4%

OP 3Qtr Bk Rs.Cr.
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean151.57479
Minimum-355.34
Maximum1864.76
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)1.4%
Memory size1.1 KiB
2024-02-29T22:54:38.369477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-355.34
5-th percentile9.55
Q126.725
median66.3
Q3161.545
95-th percentile592.74
Maximum1864.76
Range2220.1
Interquartile range (IQR)134.82

Descriptive statistics

Standard deviation276.20312
Coefficient of variation (CV)1.8222233
Kurtosis21.385238
Mean151.57479
Median Absolute Deviation (MAD)49.97
Skewness3.942303
Sum10761.81
Variance76288.162
MonotonicityNot monotonic
2024-02-29T22:54:39.190145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.53 1
 
1.4%
365.72 1
 
1.4%
174.77 1
 
1.4%
20.31 1
 
1.4%
38 1
 
1.4%
154.06 1
 
1.4%
111.15 1
 
1.4%
6.8 1
 
1.4%
203.82 1
 
1.4%
200 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
-355.34 1
1.4%
1.32 1
1.4%
1.53 1
1.4%
6.8 1
1.4%
12.3 1
1.4%
12.5 1
1.4%
12.6 1
1.4%
13.18 1
1.4%
14.76 1
1.4%
14.82 1
1.4%
ValueCountFrequency (%)
1864.76 1
1.4%
849.13 1
1.4%
770.59 1
1.4%
603.16 1
1.4%
582.32 1
1.4%
461.23 1
1.4%
415.1 1
1.4%
365.72 1
1.4%
349.51 1
1.4%
346.67 1
1.4%

OP Qtr Rs.Cr.
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean177.58746
Minimum5.42
Maximum2056.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-02-29T22:54:39.713994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.42
5-th percentile12.1
Q128.26
median67.98
Q3207.91
95-th percentile560.455
Maximum2056.09
Range2050.67
Interquartile range (IQR)179.65

Descriptive statistics

Standard deviation301.62977
Coefficient of variation (CV)1.6984857
Kurtosis22.120859
Mean177.58746
Median Absolute Deviation (MAD)51.45
Skewness4.1767293
Sum12608.71
Variance90980.519
MonotonicityNot monotonic
2024-02-29T22:54:40.095397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.34 1
 
1.4%
382.1 1
 
1.4%
243.54 1
 
1.4%
14.26 1
 
1.4%
26.84 1
 
1.4%
124.89 1
 
1.4%
198.91 1
 
1.4%
5.42 1
 
1.4%
216.91 1
 
1.4%
232.53 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
5.42 1
1.4%
6.34 1
1.4%
11.43 1
1.4%
11.52 1
1.4%
12.68 1
1.4%
13.36 1
1.4%
13.71 1
1.4%
14.26 1
1.4%
15.67 1
1.4%
16.53 1
1.4%
ValueCountFrequency (%)
2056.09 1
1.4%
1054.93 1
1.4%
913.73 1
1.4%
569.51 1
1.4%
551.4 1
1.4%
536.73 1
1.4%
496.62 1
1.4%
382.1 1
1.4%
349.26 1
1.4%
335.37 1
1.4%

profit_before_tax_Qtr_Cr
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean160.44803
Minimum4.69
Maximum1967.78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-02-29T22:54:40.397739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.69
5-th percentile10.19
Q128.255
median61.42
Q3161.54
95-th percentile560.06
Maximum1967.78
Range1963.09
Interquartile range (IQR)133.285

Descriptive statistics

Standard deviation285.29823
Coefficient of variation (CV)1.7781348
Kurtosis23.669899
Mean160.44803
Median Absolute Deviation (MAD)49.26
Skewness4.3435433
Sum11391.81
Variance81395.08
MonotonicityNot monotonic
2024-02-29T22:54:40.814750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.41 1
 
1.4%
412.5 1
 
1.4%
208.66 1
 
1.4%
9.97 1
 
1.4%
18.17 1
 
1.4%
97.5 1
 
1.4%
148.54 1
 
1.4%
4.69 1
 
1.4%
188.43 1
 
1.4%
164.15 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
4.69 1
1.4%
5.56 1
1.4%
9.93 1
1.4%
9.97 1
1.4%
10.41 1
1.4%
11.21 1
1.4%
11.31 1
1.4%
11.69 1
1.4%
11.91 1
1.4%
12.16 1
1.4%
ValueCountFrequency (%)
1967.78 1
1.4%
999.55 1
1.4%
789.14 1
1.4%
573.73 1
1.4%
546.39 1
1.4%
512.2 1
1.4%
412.5 1
1.4%
399.16 1
1.4%
305.7 1
1.4%
293.67 1
1.4%

profit_before_tax_Prev_Qtr_Cr
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean145.82085
Minimum-3.81
Maximum1650.94
Zeros0
Zeros (%)0.0%
Negative1
Negative (%)1.4%
Memory size1.1 KiB
2024-02-29T22:54:41.184953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-3.81
5-th percentile8.29
Q123.215
median65.48
Q3151.945
95-th percentile571.39
Maximum1650.94
Range1654.75
Interquartile range (IQR)128.73

Descriptive statistics

Standard deviation243.86401
Coefficient of variation (CV)1.6723536
Kurtosis20.814975
Mean145.82085
Median Absolute Deviation (MAD)45.2
Skewness4.0000969
Sum10353.28
Variance59469.655
MonotonicityNot monotonic
2024-02-29T22:54:41.538693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.27 1
 
1.4%
370.8 1
 
1.4%
194.3 1
 
1.4%
-3.81 1
 
1.4%
32.03 1
 
1.4%
96.17 1
 
1.4%
90.04 1
 
1.4%
5.98 1
 
1.4%
163.01 1
 
1.4%
149.52 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
-3.81 1
1.4%
5.98 1
1.4%
6.96 1
1.4%
7.27 1
1.4%
9.31 1
1.4%
9.51 1
1.4%
11.3 1
1.4%
11.55 1
1.4%
16.76 1
1.4%
16.81 1
1.4%
ValueCountFrequency (%)
1650.94 1
1.4%
763.65 1
1.4%
661.45 1
1.4%
585.63 1
1.4%
557.15 1
1.4%
445.4 1
1.4%
406.1 1
1.4%
379.26 1
1.4%
370.8 1
1.4%
290.22 1
1.4%

other_effect_Qtr_Cr
Real number (ℝ)

HIGH CORRELATION 

Distinct70
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8908451
Minimum-84.32
Maximum132.04
Zeros0
Zeros (%)0.0%
Negative27
Negative (%)38.0%
Memory size1.1 KiB
2024-02-29T22:54:41.940734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-84.32
5-th percentile-19.56
Q1-1.645
median0.91
Q36.8
95-th percentile39.585
Maximum132.04
Range216.36
Interquartile range (IQR)8.445

Descriptive statistics

Standard deviation25.12495
Coefficient of variation (CV)6.4574532
Kurtosis11.321027
Mean3.8908451
Median Absolute Deviation (MAD)3.27
Skewness1.2136421
Sum276.25
Variance631.26311
MonotonicityNot monotonic
2024-02-29T22:54:42.278231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.49 2
 
2.8%
4.08 1
 
1.4%
17.36 1
 
1.4%
-1.63 1
 
1.4%
-1.85 1
 
1.4%
-2.73 1
 
1.4%
-13.93 1
 
1.4%
-0.05 1
 
1.4%
54.91 1
 
1.4%
-12.92 1
 
1.4%
Other values (60) 60
84.5%
ValueCountFrequency (%)
-84.32 1
1.4%
-61.94 1
1.4%
-45.75 1
1.4%
-21.95 1
1.4%
-17.17 1
1.4%
-14.97 1
1.4%
-13.93 1
1.4%
-12.92 1
1.4%
-12.41 1
1.4%
-5.51 1
1.4%
ValueCountFrequency (%)
132.04 1
1.4%
54.91 1
1.4%
41.1 1
1.4%
40.41 1
1.4%
38.76 1
1.4%
37 1
1.4%
29.48 1
1.4%
20.46 1
1.4%
20.36 1
1.4%
18.29 1
1.4%

other_effect_Prev_Qtr_Cr
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2002817
Minimum-98.25
Maximum143.43
Zeros0
Zeros (%)0.0%
Negative26
Negative (%)36.6%
Memory size1.1 KiB
2024-02-29T22:54:42.729567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-98.25
5-th percentile-22.795
Q1-1.235
median1.31
Q38.015
95-th percentile28.005
Maximum143.43
Range241.68
Interquartile range (IQR)9.25

Descriptive statistics

Standard deviation26.379737
Coefficient of variation (CV)8.2429422
Kurtosis14.174449
Mean3.2002817
Median Absolute Deviation (MAD)3.96
Skewness1.1204299
Sum227.22
Variance695.89052
MonotonicityNot monotonic
2024-02-29T22:54:43.197188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-8.881784197 × 10-161
 
1.4%
52.01 1
 
1.4%
-6.43 1
 
1.4%
-0.76 1
 
1.4%
-3.22 1
 
1.4%
-3.21 1
 
1.4%
-8.12 1
 
1.4%
-0.09 1
 
1.4%
-26.19 1
 
1.4%
-19.4 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
-98.25 1
1.4%
-65.09 1
1.4%
-55.74 1
1.4%
-26.19 1
1.4%
-19.4 1
1.4%
-16.48 1
1.4%
-13.67 1
1.4%
-8.75 1
1.4%
-8.12 1
1.4%
-6.43 1
1.4%
ValueCountFrequency (%)
143.43 1
1.4%
52.01 1
1.4%
47.3 1
1.4%
28.47 1
1.4%
27.54 1
1.4%
25.73 1
1.4%
20.12 1
1.4%
17.89 1
1.4%
17.33 1
1.4%
16.6 1
1.4%

expenses_Qtr_Cr
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean871.46563
Minimum14.18
Maximum7047
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-02-29T22:54:43.787988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14.18
5-th percentile38.51
Q1107.32
median303.87
Q3870.93
95-th percentile4204.605
Maximum7047
Range7032.82
Interquartile range (IQR)763.61

Descriptive statistics

Standard deviation1441.0302
Coefficient of variation (CV)1.6535709
Kurtosis6.7932457
Mean871.46563
Median Absolute Deviation (MAD)241.62
Skewness2.6382365
Sum61874.06
Variance2076568
MonotonicityNot monotonic
2024-02-29T22:54:44.289181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
462.23 1
 
1.4%
912.7 1
 
1.4%
638.2 1
 
1.4%
80.89 1
 
1.4%
205.07 1
 
1.4%
858.23 1
 
1.4%
4744.27 1
 
1.4%
29.35 1
 
1.4%
1729.67 1
 
1.4%
554.94 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
14.18 1
1.4%
29.35 1
1.4%
34.07 1
1.4%
35.91 1
1.4%
41.11 1
1.4%
41.56 1
1.4%
42.19 1
1.4%
44.75 1
1.4%
44.85 1
1.4%
47.56 1
1.4%
ValueCountFrequency (%)
7047 1
1.4%
5933.2 1
1.4%
4744.27 1
1.4%
4638.25 1
1.4%
3770.96 1
1.4%
3576.72 1
1.4%
3351.49 1
1.4%
3348.78 1
1.4%
1729.67 1
1.4%
1715.25 1
1.4%

expenses_Prev_Qtr_Cr
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean823.30183
Minimum14.04
Maximum6762.34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-02-29T22:54:44.612728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14.04
5-th percentile32.7
Q1101.085
median322.03
Q3790.435
95-th percentile3517.835
Maximum6762.34
Range6748.3
Interquartile range (IQR)689.35

Descriptive statistics

Standard deviation1315.4132
Coefficient of variation (CV)1.597729
Kurtosis7.06499
Mean823.30183
Median Absolute Deviation (MAD)255.38
Skewness2.6233535
Sum58454.43
Variance1730311.9
MonotonicityNot monotonic
2024-02-29T22:54:45.000200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
323.18 1
 
1.4%
896.54 1
 
1.4%
664.09 1
 
1.4%
64.55 1
 
1.4%
587.26 1
 
1.4%
818.59 1
 
1.4%
3139.63 1
 
1.4%
31.53 1
 
1.4%
1578.71 1
 
1.4%
511.4 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
14.04 1
1.4%
21.68 1
1.4%
28.69 1
1.4%
31.53 1
1.4%
33.87 1
1.4%
40.21 1
1.4%
40.44 1
1.4%
47.3 1
1.4%
47.36 1
1.4%
50.62 1
1.4%
ValueCountFrequency (%)
6762.34 1
1.4%
4987.82 1
1.4%
4507.41 1
1.4%
3608.78 1
1.4%
3426.89 1
1.4%
3393.51 1
1.4%
3387.06 1
1.4%
3139.63 1
1.4%
1837.26 1
1.4%
1578.71 1
1.4%

Interactions

2024-02-29T22:54:20.348983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:51.942782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:56.536507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:01.416229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:05.893611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:11.019265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:16.187843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:21.077315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:26.120031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:31.097063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:35.899934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:41.311776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:45.837236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:50.252527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:54.712468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:00.613743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:05.618860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:10.201802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:15.424786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:20.626411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:52.304884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:56.736554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:01.666615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:06.163136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:11.386835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:16.505461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:21.251567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:26.345272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:31.378904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:36.115649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:41.523375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:46.028522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:50.477122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:54.968249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:00.918015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:05.880251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:10.477828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:15.720215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:20.923879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:52.571293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:57.013472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:01.921391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:06.458602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:11.704769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:16.802335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:21.506068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:26.683651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:31.630276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:36.296380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:41.744736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:46.174015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:50.732605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:55.285112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:01.221861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:06.157723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:10.786502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:15.946922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:21.166150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:52.843846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:57.201865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:02.132777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:06.664243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:12.008923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:17.039817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:21.730234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:26.886697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:31.861593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:36.467364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:42.048245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:46.405731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:50.970047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:55.542347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:01.437608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:06.410212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:11.042082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:16.223874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:21.405101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:53.071292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:57.418250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:02.332562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:06.830984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:12.314815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:17.304660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:22.314811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:27.156884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:32.012207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:36.721582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:42.274289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:46.671666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:51.231897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:55.789696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:01.691664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:06.639569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:11.308521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:16.445788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:21.692895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:53.274130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:57.633873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:02.578254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:07.071244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:12.748257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:17.603617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:22.601068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:27.515472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:32.217422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:37.044059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:42.565539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:46.974568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:51.522377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:56.122654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:01.988077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:06.951705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:11.625990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:16.691807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:21.950944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:53.501215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:57.888135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:02.812806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:07.320333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:13.006236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:17.828456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:22.832341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:27.780946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:32.498591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:37.321342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:42.800210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:47.257326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:51.767982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:56.426094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:02.280227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:07.207351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:11.933872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:17.007050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:22.789549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:53.799100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:58.081189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:03.169420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:07.604796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:13.193753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:18.078173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:23.100317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:28.032435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:32.751978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:37.610584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:43.037673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:47.545148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:52.003576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:56.721138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:02.533152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:07.489015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:12.215073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:17.271218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:23.082257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:54.017647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:58.337297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:03.439548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:07.799146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:13.468865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:18.329412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:23.336899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:28.267824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:33.021537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:37.925605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:43.296558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:47.776453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:52.169175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:57.025282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:02.796850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:07.719574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:12.471930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:17.415873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:23.365793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:54.219876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:58.554598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:03.691148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:08.024780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:13.736404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:18.548360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:23.540840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:28.532853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:33.240684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:38.613932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:43.553219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:48.029572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:52.368040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:57.295746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:03.051452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:07.908346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:12.742164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:17.698108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:23.581237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:54.504593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:58.894369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:03.916447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:08.309744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:14.019090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:18.829557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:23.808927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:28.813727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:33.556966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:38.911299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:43.775240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:48.287201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:52.624876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:58.078826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:03.354480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:08.167361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:13.068831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:17.983591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:23.795215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:54.717598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:59.154970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:04.148203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:08.626242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:14.230165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:19.104832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:24.064426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:29.026647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:33.744883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:39.204462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:44.047851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:48.527098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:52.817521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:58.371852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:03.568042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:08.407219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:13.342546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:18.186945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:24.021163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:54.884820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:59.348619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:04.350622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:08.871710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:14.460702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:19.366803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:24.250802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:29.251504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:33.996320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:39.377813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:44.221416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:48.738153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:53.032243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:58.616059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:03.823394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:08.621102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:13.562656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:18.448986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:24.239312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:55.083251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:59.757286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:04.574414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:09.136613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:14.685513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:19.576784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:24.423157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:29.518914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:34.279493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:39.615082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:44.453806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:48.875602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:53.262311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:58.892829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:04.072899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:08.782550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:13.797747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:18.741014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:24.555473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:55.355174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:00.005177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:04.823076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:09.724424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:14.992423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:19.861381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:24.754261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:29.846266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:34.505824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:39.959837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:44.678249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:49.041274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:53.555203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:59.214552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:04.362326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:09.052991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:14.089958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:18.966291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:24.814822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:55.615106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:00.291796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:05.091305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:09.976797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:15.247471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:20.140532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:25.055924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:30.097501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:34.783541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:40.194846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:44.924744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:49.279694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:53.823075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:59.470294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:04.589847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:09.337308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:14.369565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:19.256521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:25.001857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:55.838146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:00.541608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:05.296713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:10.229445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:15.436325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:20.374276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:25.325288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:30.334406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:35.036597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:40.413869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:45.175558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:49.493689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:54.036348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:59.765883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:04.832002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:09.569035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:14.627430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:19.514345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:25.269753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:56.061999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:00.820272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:05.547931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:10.465087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:15.691228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:20.584844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:25.513321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:30.551539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:35.304342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:40.727905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:45.387725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:49.724917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:54.282096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:00.001521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:05.107880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:09.768024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:14.899825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:19.761999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:25.551080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:52:56.329441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:01.111562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:05.737788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:10.731744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:15.944031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:20.817300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:25.780046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:30.818378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:35.607281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:41.061940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:45.614932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:50.024458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:53:54.486525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:00.343465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:05.355841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:10.017725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:15.164001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-29T22:54:20.044660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-02-29T22:54:45.431297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Mar Cap Rs.Cr.NP 2Qtr Bk Rs.Cr.NP 3Qtr Bk Rs.Cr.NP Prev Qtr Rs.Cr.NP Qtr Rs.Cr.OP 2Qtr Bk Rs.Cr.OP 3Qtr Bk Rs.Cr.OP Prev Qtr Rs.Cr.OP Qtr Rs.Cr.Sales 2Qtr Bk Rs.Cr.Sales 3Qtr Bk Rs.Cr.Sales Prev Qtr Rs.Cr.Sales Qtr Rs.Cr.expenses_Prev_Qtr_Crexpenses_Qtr_Crother_effect_Prev_Qtr_Crother_effect_Qtr_Crprofit_before_tax_Prev_Qtr_Crprofit_before_tax_Qtr_Cr
Mar Cap Rs.Cr.1.0000.8200.8600.8700.8820.8450.7720.8700.8810.7920.7970.8080.8160.7780.7820.2550.1560.8740.884
NP 2Qtr Bk Rs.Cr.0.8201.0000.9540.9490.9380.9830.8800.9550.9310.9020.8970.8700.8660.8350.8270.3400.2510.9480.931
NP 3Qtr Bk Rs.Cr.0.8600.9541.0000.9490.9400.9520.9000.9540.9430.8980.9080.8900.8870.8590.8520.3370.2430.9520.940
NP Prev Qtr Rs.Cr.0.8700.9490.9491.0000.9620.9550.8690.9830.9430.8990.9020.9000.8830.8610.8430.3680.2840.9980.955
NP Qtr Rs.Cr.0.8820.9380.9400.9621.0000.9400.8630.9640.9800.8760.8780.8760.8920.8350.8420.3140.2320.9660.995
OP 2Qtr Bk Rs.Cr.0.8450.9830.9520.9550.9401.0000.8950.9690.9410.9230.9190.8990.8930.8660.8580.2920.1950.9550.934
OP 3Qtr Bk Rs.Cr.0.7720.8800.9000.8690.8630.8951.0000.8840.8710.8330.8380.8170.8150.7850.7790.2130.1020.8690.857
OP Prev Qtr Rs.Cr.0.8700.9550.9540.9830.9640.9690.8841.0000.9700.9140.9160.9130.9010.8740.8580.2760.1980.9820.963
OP Qtr Rs.Cr.0.8810.9310.9430.9430.9800.9410.8710.9701.0000.8840.8890.8870.9010.8510.8500.2400.1520.9490.987
Sales 2Qtr Bk Rs.Cr.0.7920.9020.8980.8990.8760.9230.8330.9140.8841.0000.9920.9770.9560.9700.9540.2290.1510.8970.873
Sales 3Qtr Bk Rs.Cr.0.7970.8970.9080.9020.8780.9190.8380.9160.8890.9921.0000.9870.9670.9810.9660.2530.1840.9020.878
Sales Prev Qtr Rs.Cr.0.8080.8700.8900.9000.8760.8990.8170.9130.8870.9770.9871.0000.9780.9940.9750.2570.1900.9000.879
Sales Qtr Rs.Cr.0.8160.8660.8870.8830.8920.8930.8150.9010.9010.9560.9670.9781.0000.9710.9900.2480.1800.8890.896
expenses_Prev_Qtr_Cr0.7780.8350.8590.8610.8350.8660.7850.8740.8510.9700.9810.9940.9711.0000.9790.2410.1760.8610.839
expenses_Qtr_Cr0.7820.8270.8520.8430.8420.8580.7790.8580.8500.9540.9660.9750.9900.9791.0000.2490.1860.8480.844
other_effect_Prev_Qtr_Cr0.2550.3400.3370.3680.3140.2920.2130.2760.2400.2290.2530.2570.2480.2410.2491.0000.9010.3760.302
other_effect_Qtr_Cr0.1560.2510.2430.2840.2320.1950.1020.1980.1520.1510.1840.1900.1800.1760.1860.9011.0000.2940.221
profit_before_tax_Prev_Qtr_Cr0.8740.9480.9520.9980.9660.9550.8690.9820.9490.8970.9020.9000.8890.8610.8480.3760.2941.0000.962
profit_before_tax_Qtr_Cr0.8840.9310.9400.9550.9950.9340.8570.9630.9870.8730.8780.8790.8960.8390.8440.3020.2210.9621.000

Missing values

2024-02-29T22:54:26.063429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-29T22:54:26.717060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

NameMar Cap Rs.Cr.NP Qtr Rs.Cr.Sales Qtr Rs.Cr.Sales Prev Qtr Rs.Cr.NP 2Qtr Bk Rs.Cr.NP 3Qtr Bk Rs.Cr.NP Prev Qtr Rs.Cr.Sales 2Qtr Bk Rs.Cr.Sales 3Qtr Bk Rs.Cr.OP Prev Qtr Rs.Cr.OP 2Qtr Bk Rs.Cr.OP 3Qtr Bk Rs.Cr.OP Qtr Rs.Cr.profit_before_tax_Qtr_Crprofit_before_tax_Prev_Qtr_Crother_effect_Qtr_Crother_effect_Prev_Qtr_Crexpenses_Qtr_Crexpenses_Prev_Qtr_Cr
0Remedium Life1054.756.53468.57330.46-4.781.525.2575.58176.487.28-2.901.536.3410.417.274.08-8.881784e-16462.23323.18
1Waaree Renewab.5968.9118.29150.06128.9412.2724.9811.1061.4973.8828.0915.9822.2987.8140.3917.93-45.75-8.750000e+0062.25100.85
2Dreamfolks Servi2773.7318.14282.47266.3025.3218.9813.09237.74204.0017.7833.7426.0524.9324.2817.790.278.700000e-01257.54248.52
3Jyoti Resins1848.3616.1862.9661.1816.4112.1515.7365.0866.6120.7420.0516.3321.4021.9421.030.815.600000e-0141.5640.44
4Esab India8616.0938.41303.14298.2541.8636.3142.38301.68267.3957.7956.7148.4354.4052.0556.881.052.430000e+00248.74240.46
5Fine Organic14008.85103.37540.49547.17149.45106.2399.77596.63759.54140.50201.76159.32130.25132.27142.5716.421.379000e+01410.24406.67
6Crest Ventures1008.8532.1761.1831.0412.229.265.8530.2026.5617.0014.0016.0047.0040.849.51-5.00-6.340000e+0014.1814.04
7Shilchar Tech.2075.9124.40106.2767.2216.2811.8916.3894.9968.2719.9221.1714.7629.6832.6021.783.562.510000e+0076.5947.30
8West Coast Paper4853.00218.551193.841138.62320.95310.98278.351357.481239.16394.52492.52461.23310.21293.67379.2629.482.847000e+01883.63744.10
9Share India Sec.6070.05112.62366.38277.31106.8992.5282.27340.72275.80175.99124.57154.20182.51157.29108.23-21.95-6.509000e+01183.87101.32
NameMar Cap Rs.Cr.NP Qtr Rs.Cr.Sales Qtr Rs.Cr.Sales Prev Qtr Rs.Cr.NP 2Qtr Bk Rs.Cr.NP 3Qtr Bk Rs.Cr.NP Prev Qtr Rs.Cr.Sales 2Qtr Bk Rs.Cr.Sales 3Qtr Bk Rs.Cr.OP Prev Qtr Rs.Cr.OP 2Qtr Bk Rs.Cr.OP 3Qtr Bk Rs.Cr.OP Qtr Rs.Cr.profit_before_tax_Qtr_Crprofit_before_tax_Prev_Qtr_Crother_effect_Qtr_Crother_effect_Prev_Qtr_Crexpenses_Qtr_Crexpenses_Prev_Qtr_Cr
64Hind.Oil Explor.2489.4643.18112.83167.61106.6537.3466.07175.09169.8390.18135.4679.6167.9844.1067.61-5.51-2.5144.8577.43
65Affle India17342.6666.78431.30406.5862.3869.1266.17355.82376.0678.1169.0080.3287.2373.1970.074.406.38344.07328.47
66Transpek Inds.1156.232.99120.94162.1622.3724.7215.85202.76196.4722.5140.1442.1813.365.5621.251.037.52107.58139.65
67Granules India10143.18102.121189.49985.52119.61124.3347.901195.501146.13212.97136.82228.11250.49136.0365.48-61.94-98.25939.00772.55
68Poly Medicure13860.1462.19337.29320.8358.8150.0162.70306.85284.8387.2083.2171.0384.2380.9483.0412.7011.36253.06233.63
69Vidhi Specialty2073.719.0980.1579.678.867.688.3889.4786.4113.0212.2012.6013.7111.6911.55-0.64-0.5066.4466.65
70ADF Foods2232.4614.93124.62112.4216.0918.5214.73123.11123.2321.9326.4627.0721.7720.5720.282.491.93102.8590.49
71Latent View9631.1426.3071.7768.9029.7137.3626.3869.6068.4621.5425.9127.1324.2136.8836.2314.6216.6047.5647.36
72Aarti Drugs4963.8434.58577.54591.6353.1736.7139.54696.41625.5365.4271.9188.5259.7446.8353.04-1.13-0.63517.80526.21
73IOL Chemicals2648.4937.79545.30563.1865.2724.1546.21587.21523.4872.8695.7943.0464.1051.1061.532.673.11481.20490.32